Data Governance

To identify all governing rules and regulations, to continuously protect the interests of data stakeholders and to meditate and settle any issues as a result of disobedience to the said rules and regulations are the three main mission of Data Governance. These missions of Date Governance reflect those greatly affected by the process, specifically those data stakeholders and other participants.  To simply yet fully comprehend the mission and vision of Data Governance, let us take the example of on of the most common organization- a bicameral government.

Data governance operates like this kind of government with its three separate branches: the executive branch, legislative branch and the judicial branch- all having their own duties, functions, and checks & balances. For background, the legislative passes, makes and even changes laws, the judicial branch interprets these laws specifically in terms of settling and resolving issues and the executive branch makes sure that these laws are followed and reinforced while providing all services to its constituents.

On the other hand, Data Stakeholders are like citizens particularly in terms on their rights, privileges and obligations. Just like a citizen whose actions is governed by laws, Data Stakeholders should be aware that there are rules governing their actions when it comes to traveling to different data domains. And they are also liable and can be sanctioned according to the rules set by the Data Governance office.

Those in the lower level can have their own mission specifically for their type of program and data. However, these specific missions must still be in accordance or in response to the general three missions of Data Governance.

Along with mission is vision, which should also be concise and comprehensible. When crafting your program’s visions, use inspiring words that can entice and persuade Data Stakeholders to set their own data-related goals.

Data Governance is the lifeblood of an enterprise.  Why?  It is mainly because a business cannot stand on its own without its patrons.  These customers vary in demographics; hence, their personal information varies from one another.  The quality of customer information tends to dwindle due to the number of sources where the information comes from. The more we get the information “close to the source”, the better the quality of information that we gather all-together.  

In order to achieve utmost data quality, it has to start from the bottom-up. An enterprise needs to solidify and integrate this information into one silo and create processes and profiles to collect the data upstream.  Effective Data Governance requires that customer information be available where need be at the most opportune time when it is needed. Data should be centralized in a way that it would be easy for the Data Stewards to look for information and make necessary changes where applicable.

We need to gain a complete and timely understanding of our customers in order to effectively gather information. We need to know which information is needed at a given time. When all the needed information has already been collected, it should be compiled and consolidated into one big effective structure that can easily be accessed by people within the organization.  To reduce operational risks, and to lessen situations where customers get irate because of wrong information given to them, Data Quality should (as always) be observed. This regulating body ensures that various processes are being met in order to provide a flawless data structure.

A unified front end system must be employed by every enterprise if they want to maintain the integrity of their systems and their data.  With the overwhelming amount of information from both internal and external customers, Global organizations should start to see Data Governance not only as a single entity in an enterprise but its vital importance to the welfare of the enterprise as a whole.